Analytics for Tracking Student Engagement

Abstract

Although there has been much research in the area of data analytics in recent years (e.g. Shum and Ferguson 2012), there are questions regarding which analytic methodologies can be most effective in informing higher education teaching and learning practices (Gibson and de Freitas, 2016). This project focuses on one module within the School of Computing and Communications in the STEM faculty to gain a clearer understanding on why students might, or might not, engage with computer aided learning and teaching (TELT) resources. We explore the use of specific TELT resources on the module ‘Communications Technology’, a print-based module with a range of online resources designed to supplement the text. The research questions cover two key areas; the effectiveness of the analytics tools and students’ perception of the TELT resources. Via data analytics we can review: • When the students engage with the TELT resources and whether this is at predicted times during the module. • Whether students revisit the TELT resources. Via individual student feedback we can explore: • What motivates students to engage with TELT resources. • Whether students understand topic more deeply as a result of using TELT resources. • If students are deterred if the resources are too complicated/time consuming. The findings should be of interest to module teams across many universities. This project will build on previous work undertaken in this area, e.g. Herodotou et al (2017) and Tempelaar et al (2017), and contribute to the wider body of knowledge in the area of data analytics.